hagabbar / Glasgow_Machine_Learning_Course-2019Links
A hands-on machine learning course for physics and astronomy PhD students at the University of Glasgow. Courses designed by John Armstrong and Hunter Gabbard.
☆14Updated 6 years ago
Alternatives and similar repositories for Glasgow_Machine_Learning_Course-2019
Users that are interested in Glasgow_Machine_Learning_Course-2019 are comparing it to the libraries listed below
Sorting:
- Notebooks for PHYS 440/540 at Drexel University☆16Updated last year
- Hadronic Interaction Model interface in PYthon☆41Updated last week
- Machine Learning for Physics and Astronomy☆66Updated 3 years ago
- HEP/Astroparticle/Astrophysics/Cosmology open source packages. Community effort. Physics people, unite!☆143Updated 3 months ago
- A collection of research notebooks in *cosmology*.☆23Updated 2 months ago
- Pythonic Bayesian inference and visualization for the MultiNest Nested Sampling Algorithm and PyCuba's cubature algorithms.☆213Updated last year
- ☆22Updated 2 years ago
- Machine learning and statistics for physicists☆101Updated 4 years ago
- Dynamics of spinning black-hole binaries with python☆38Updated 5 months ago
- PhD class "Black Holes and Gravitational Waves"; University of Birmingham and MPAGS☆16Updated 5 years ago
- Code for efficiently computing 2-point and 3-point correlation functions. For documentation, go to☆109Updated 4 months ago
- Theoretical models of kilonova presented in Kasen et al, Nature, 2017☆23Updated 7 years ago
- Generates initial conditions for cosmological N-body simulations, optionally applying Particle Linear Theory corrections.☆14Updated 3 weeks ago
- MultiNest is a Bayesian inference tool which calculates the evidence and explores the parameter space which may contain multiple posterio…☆69Updated 2 years ago
- Learn how to use PyCBC to analyze gravitational-wave data and do parameter inference.☆144Updated last month
- Error analysis, diagnostic tests and plots for nested sampling calculations.☆16Updated 2 years ago
- Github repository for "Big Data in Astrophysics" - Spring 2021☆14Updated 4 years ago
- ☆77Updated last year
- Mirror of LALSuite, please use official GitLab repository.☆27Updated this week
- Large suite of N-body simulations☆97Updated last month
- Matplotlib template for SuperMongo style 🔭☆138Updated last month
- ☆16Updated 4 years ago
- Fit and compare complex models reliably and rapidly. Advanced nested sampling.☆195Updated last week
- Matplotlib tutorials☆132Updated last year
- Analysis kit for large-scale structure datasets, the massively parallel way☆118Updated 2 months ago
- Plots for DM-nucleus and DM-electron scattering experiments☆15Updated 9 months ago
- encore: Efficient isotropic 2-, 3- and 4-point correlation functions in C++ and CUDA☆21Updated 4 months ago
- Course notes and resources for Stanford University graduate course PHYS366: Statistical Methods in Astrophysics☆121Updated last year
- Likelihood-Free Inference for Gravitational Waves☆42Updated 4 years ago
- Materials related to AST1420 at the University of Toronto☆21Updated last year